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Liu-Xiang
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sql-code-llama

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Safetensors
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Training in progress, step 20

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  1. README.md +22 -7
  2. adapter_model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -16,7 +16,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [codellama/CodeLlama-7b-hf](https://huggingface.co/codellama/CodeLlama-7b-hf) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.5699
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  ## Model description
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@@ -44,17 +44,32 @@ The following hyperparameters were used during training:
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_steps: 100
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- - training_steps: 100
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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- | 2.1594 | 0.04 | 20 | 1.9765 |
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- | 1.1079 | 0.07 | 40 | 0.8140 |
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- | 0.8124 | 0.11 | 60 | 0.6610 |
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- | 0.5827 | 0.14 | 80 | 0.5901 |
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- | 0.4148 | 0.18 | 100 | 0.5699 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [codellama/CodeLlama-7b-hf](https://huggingface.co/codellama/CodeLlama-7b-hf) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.4621
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  ## Model description
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_steps: 100
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+ - training_steps: 400
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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+ | 2.1563 | 0.04 | 20 | 1.9767 |
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+ | 1.1222 | 0.07 | 40 | 0.8267 |
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+ | 0.814 | 0.11 | 60 | 0.6637 |
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+ | 0.5956 | 0.14 | 80 | 0.5908 |
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+ | 0.405 | 0.18 | 100 | 0.5643 |
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+ | 0.5643 | 0.22 | 120 | 0.5204 |
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+ | 0.4326 | 0.25 | 140 | 0.5107 |
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+ | 0.6401 | 0.29 | 160 | 0.5211 |
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+ | 0.4789 | 0.33 | 180 | 0.4908 |
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+ | 0.3577 | 0.36 | 200 | 0.5069 |
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+ | 0.5289 | 0.4 | 220 | 0.4851 |
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+ | 0.3971 | 0.43 | 240 | 0.4811 |
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+ | 0.5972 | 0.47 | 260 | 0.4807 |
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+ | 0.4683 | 0.51 | 280 | 0.4712 |
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+ | 0.3442 | 0.54 | 300 | 0.4790 |
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+ | 0.5148 | 0.58 | 320 | 0.4692 |
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+ | 0.3917 | 0.62 | 340 | 0.4661 |
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+ | 0.5769 | 0.65 | 360 | 0.4661 |
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+ | 0.4603 | 0.69 | 380 | 0.4629 |
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+ | 0.3461 | 0.72 | 400 | 0.4621 |
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  ### Framework versions
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